import {z} from 'zod'

export type GetApiV1TrainingJobsArgs = {type?: ('config' | 'interactive' | null) | undefined, status?: (string | null) | undefined, project_id?: (string | null) | undefined, limit?: number | undefined, offset?: number | undefined};

export type GetApiV1TrainingJobsOptions = {baseUrl?: string | undefined, ApiKeyAuth?: string | undefined, fetch?: typeof fetch | undefined};

export const datasetReference = z.object({name: z.string(), version: z.string().nullable().optional()});

export const trainingNotice = z.object({code: z.string(), message: z.string()});

export const trainingJobResponse = z.object({artifact_ready: z.boolean().nullable().optional(), base_model: z.string(), batch_size: z.number().int().nullable(), completed_at: z.string().nullable().optional(), created_at: z.string(), current_epoch: z.number().int().nullable().optional(), datasets: z.array(datasetReference), deployability_reason: z.string().nullable().optional(), deployment_status: z.string().nullable(), error_message: z.string().nullable().optional(), example: z.string().nullable().optional(), experiment_id: z.string().nullable().optional(), hub_model_id: z.string().nullable().optional(), hub_model_private: z.boolean().nullable().optional(), id: z.string(), instance_type: z.string().nullable().optional(), is_deployable: z.boolean().nullable().optional(), is_terminal_status: z.boolean().nullable().optional(), job_reference: z.string().nullable().optional(), labels: z.array(z.string()).nullable().optional(), learning_rate: z.number().nullable(), metrics: z.record(z.string(), z.unknown()).nullable().optional(), model_auto_selected: z.boolean().nullable().optional(), model_kind: z.enum(["lora", "full"]).nullable().optional(), model_name: z.string().nullable().optional(), model_selection_reason: z.string().nullable().optional(), normalized_status: z.string().nullable().optional(), notices: z.array(trainingNotice).optional(), nr_epochs: z.number().int().nullable(), progress_percent: z.number().int().nullable().optional(), project_id: z.string().nullable().optional(), provider_deployments: z.record(z.string(), z.unknown()).nullable().optional(), provider_name: z.string().nullable().optional(), provider_ready: z.boolean().nullable().optional(), resolved_recipe: z.record(z.string(), z.unknown()).nullable().optional(), root_job_id: z.string().nullable().optional(), seed: z.number().int().nullable().optional(), source: z.enum(["config_training", "interactive_checkpoint"]).optional(), started_at: z.string().nullable().optional(), status: z.string(), task_type: z.string().nullable().optional(), trained_model_path: z.string().nullable().optional(), training_type: z.string().nullable().optional(), type: z.literal("config").optional(), updated_at: z.string(), user_id: z.string(), validation_data_percentage: z.number().nullable(), version_number: z.string().nullable().optional()});

export const checkpointView = z.object({checkpoint_id: z.string(), checkpoint_type: z.enum(["training", "sampler"]), expires_at: z.string().nullable().optional(), public: z.boolean().optional(), size_bytes: z.number().int().nullable().optional(), time: z.string(), tinker_path: z.string(), user_metadata: z.record(z.string(), z.string()).nullable().optional()});

export const interactiveJobView = z.object({base_model: z.string(), corrupted: z.boolean().optional(), created_at: z.string(), error_message: z.string().nullable().optional(), id: z.string(), is_lora: z.boolean().optional(), is_terminal_status: z.boolean(), job_id: z.string(), last_checkpoint: checkpointView.nullable().optional(), last_request_time: z.string(), last_sampler_checkpoint: checkpointView.nullable().optional(), lora_rank: z.number().int().nullable().optional(), model_owner: z.string(), status: z.enum(["creating", "active", "stopping", "stopped", "failed"]), stop_reason: z.enum(["requested", "idle_timeout", "session_finished", "session_errored"]).nullable().optional(), training_run_id: z.string(), type: z.literal("interactive").optional(), user_metadata: z.record(z.string(), z.string()).nullable().optional()});

export const trainingJobsPage = z.object({count: z.number().int(), has_more: z.boolean(), success: z.boolean().optional(), total: z.number().int(), training_jobs: z.array(z.discriminatedUnion("type", [trainingJobResponse, interactiveJobView]))});

export const validateResponse = async <Output>(
  schema: {
    readonly '~standard': {
      readonly validate: (value: unknown) => ({ readonly value: Output; readonly issues?: undefined } | { readonly issues: ReadonlyArray<{ readonly message: string; readonly path?: ReadonlyArray<PropertyKey | { readonly key: PropertyKey }> | undefined }> }) | Promise<{ readonly value: Output; readonly issues?: undefined } | { readonly issues: ReadonlyArray<{ readonly message: string; readonly path?: ReadonlyArray<PropertyKey | { readonly key: PropertyKey }> | undefined }> }>
    }
  },
  value: unknown
): Promise<Output> => {
  const result = await schema['~standard'].validate(value)

  if (result.issues !== undefined) {
    const detail = result.issues
      .map(({ message, path }) =>
        path?.length
          ? `${path.map((segment) => String(typeof segment === 'object' ? segment.key : segment)).join('.')}: ${message}`
          : message
      )
      .join('; ')

    throw new Error(`Response does not match the schema: ${detail}`, { cause: { issues: result.issues } })
  }

  return result.value
};

/**
 * List Jobs
 * 
 * GET /v1/training/jobs
 * 
 * Also accepts auth: BearerAuth
 */
export const getApiV1TrainingJobs = async (args: GetApiV1TrainingJobsArgs, options?: GetApiV1TrainingJobsOptions) => {
const {baseUrl = "https://api.fastino.ai", fetch: fetchFn = fetch, ApiKeyAuth} = options ?? {}

const query = new URLSearchParams()
const headers = new Headers()
headers.set('accept', "application/json")

if (args.type != null) query.append("type", String(args.type))
if (args.status != null) query.append("status", String(args.status))
if (args.project_id != null) query.append("project_id", String(args.project_id))
if (args.limit != null) query.append("limit", String(args.limit))
if (args.offset != null) query.append("offset", String(args.offset))
if (ApiKeyAuth !== undefined) headers.set("X-API-Key", ApiKeyAuth)

const url = `${baseUrl.replace(/\/+$/, '')}/v1/training/jobs${query.size > 0 ? `?${query}` : ''}`

const res = await fetchFn(url, {method: "GET", headers})

if (!res.ok) throw new Error(`Request failed with status ${res.status}`, {cause: {status: res.status, body: await res.text()}})

return validateResponse(trainingJobsPage, await res.json())
};